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Technical Account Manager - AI Infrastructure

Primeintellect
CompanyPrimeintellect
CategoryData & Analytics
LocationSan Francisco
RemoteOn-site (inferred)
EmploymentNot stated
LevelManager
SalaryNot stated by the employer
Posted8 Jul 2026
Last verified9 Aug 2026
SourceEmployer ATS (ashby)
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Description
TECHNICAL ACCOUNT MANAGER OWN YOUR INTELLIGENCE Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own. Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet. Your Role Prime Intellect serves some of the most sophisticated AI teams in the world that depend on our compute and infrastructure to train and deploy production AI systems. The Customer Success Manager is the person who makes sure those customers succeed, scale, and keep building with us. This is not a traditional Customer Success role. Our customers run large-scale training jobs, scale inference workloads against real production traffic, and depend on cluster reliability and performance the way most companies depend on their cloud provider. The work spans the technical and the commercial — you'll be reading Grafana dashboards and discussing cluster performance with a customer's ML infrastructure team in the morning, and partnering with Sales on a capacity expansion in the afternoon. You'll own a portfolio of enterprise customers end-to-end and build the relationships that make Prime Intellect the partner of choice for their AI infrastructure. Responsibilities Customer Ownership - Own a portfolio of enterprise customers end-to-end — adoption, retention, expansion, and overall health - Build deep relationships with technical and executive stakeholders at each customer, from ML engineers to engineering leadership - Drive customer outcomes: faster time-to-value on first workloads, smooth scaling as their usage grows, and meaningful expansion as their AI ambitions expand Technical Partnership - Understand each customer's training and inference workloads at a real technical level — what models they're training, what infrastructure they need, what their performance bottlenecks are - Partner with customers' engineering teams on cluster performance, capacity planning, workload optimization, and migration - Translate customer needs into clear, prioritized feedback for our Engineering and Product teams Expansion & Renewals - Identify expansion opportunities ahead of the customer — anticipate scaling needs, surface new use cases, drive adoption of new products (Lab, Inference, additional compute capacity) - Partner with Sales on renewal conversations and growth motions - Maintain visibility into the economics of each customer relationship, in partnership with Finance and Compute Operational Excellence - Serve as the first line for customer-facing operational issues — usage questions, capacity changes, SLA tracking, incident communications - Build the cross-functional conne